Hyperphosphatemia and its Relationship with Blood Pressure, Vasoconstriction, and Endothelial Cell Dysfunction in Hypertensive Hemodialysis Patients

Hyperphosphatemia and its Relationship with Blood Pressure, Vasoconstriction, and Endothelial Cell Dysfunction in Hypertensive Hemodialysis Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hyperphosphatemia and its Relationship with Blood Pressure, Vasoconstriction, and Endothelial Cell Dysfunction in Hypertensive Hemodialysis Patients Jinwoo Jung, Haekyung Jeon-Slaughter, Hang Nguyen, Jiten Patel, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1523519/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Hyperphosphatemia occurs frequently in end-stage renal disease patients on hemodialysis and is associated with increased mortality. Hyperphosphatemia contributes to vascular calcification in these patients, but there is emerging evidence that it is also associated with endothelial cell dysfunction. Methods We conducted a cross-sectional study in hypertensive hemodialysis patients. We obtained pre-hemodialysis measurements of total peripheral resistance index (TPRI, non-invasive cardiac output monitor) and plasma levels of endothelin-1 (ET-1) and asymmetric dimethylarginine (ADMA). We ascertained the routine peridialytic blood pressure (BP) measurements from that treatment and the most recent pre-hemodialysis serum phosphate levels. We used generalized linear regression analyses to determine independent associations between serum phosphate with BP, TPRI, ET-1, and ADMA while controlling for demographic variables, parathyroid hormone (PTH), and interdialytic weight gain. Results There were 54 patients analyzed. Mean pre-HD supine and seated systolic and diastolic BP were 164 (27), 158 (21), 91.5 (17), and 86.1 (16) mmHg. Mean serum phosphate was 5.89 (1.8) mg/dL. There were significant correlations between phosphate with all pre-hemodialysis BP measurements (r=0.3, p=.04; r=0.4, p=.002; r=0.5, p<.0001; and r=0.5, p=.0003.) The correlations with phosphate and TPRI, ET-1, and ADMA were 0.3 (p=.01), 0.4 (p=.007), and 0.3 (p=.04). In our final linear regression analyses controlling for baseline characteristics, PTH, and interdialytic weight gain, independent associations between phosphate with pre-hemodialysis diastolic BP, TPRI, and ET-1 were retained (β=4.33, p=.0002; log transformed β=0.05, p=.005; reciprocal transformed β= -0.03, p=.047). Conclusions Serum phosphate concentration is independently associated with higher pre-HD BP, vasoconstriction, and markers of endothelial cell dysfunction. These findings demonstrate an additional negative impact of hyperphosphatemia on cardiovascular health beyond vascular calcification. The study was part of a registered clinical trial, NCT01862497 (May 24, 2013). Phosphate Hemodialysis Endothelial Cell Dysfunction Mineral Bone Disease Vasoconstriction Figures Figure 1 Introduction Mineral bone disease (MBD) is a non-traditional cardiovascular disease risk factor that contributes to the high mortality rate among end stage renal disease (ESRD) patients on hemodialysis (HD). Hyperphosphatemia and the related increases in parathyroid hormone (PTH) are each independently associated with mortality in this population[ 1 ]. Chronically elevated serum phosphate contributes to structural changes in blood vessels including vascular calcification, but it is also likely to be associated with other functional abnormalities of the blood vessels that may be more easily reversible. Recent experimental evidence shows that acute increases in phosphate both in vitro and in healthy individuals can induce acute endothelial cell dysfunction (ECD)[ 2 ]. The most common clinical scenario where hyperphosphatemia is observed is in advanced chronic kidney disease, especially ESRD. Compared to healthy individuals, ESRD patients also have a much higher risk of hypertension and more severe ECD[ 3 , 4 ] with ECD markers such as asymmetric dimethylarginine (ADMA) being predictive of increased mortality [ 5 ]. Despite this, there is little data on the relationship between phosphate and adverse cardiovascular consequences beyond vascular calcification. A better understanding of these relationships is needed to provide a more comprehensive approach to addressing mortality risk reduction in ESRD patients. We hypothesized that elevated serum phosphate would be independently associated with blood pressure (BP), as well as measurements of vasoconstriction and markers of ECD in hypertensive hemodialysis patients. We analyzed these associations within a cohort of patients receiving maintenance HD. Materials And Methods Study Participants We used previously collected data from a prospective cohort of hypertensive ESRD patients on maintenance HD to conduct a cross-sectional study of some of the baseline measurements. The intent of the primary study was to determine the association between intradialytic changes in total peripheral resistance index (TPRI) with ambulatory BP in hypertensive hemodialysis patients. Study inclusion criteria for the original study were 1) age > 18 years, 2) HD vintage > 1 month, and 3) peri-dialytic hypertension defined as pre-HD systolic BP > 140 mmHg or post-HD systolic BP > 130 mmHg[ 6 ]. Exclusion criteria were defined by the presence of a cardiac defibrillator or pacemaker, arm or leg amputation, coronary artery stent, implanted metallic prosthesis, pregnancy, or the inability to achieve estimated dry weight defined by the nephrologist providing the clinical care. The first 36 participants enrolled had either recurrent increases in systolic BP from pre to post-HD > 10 mmHg (n = 18) or recurrent decreases in systolic BP from pre to post-HD > 10 mmHg (n = 18). Subsequent enrollment did not require any specific intradialytic BP pattern as long as other inclusion and exclusion criteria were fulfilled. The University of Texas Southwestern Medical Center Institutional Review Board approved the protocol, and all procedures were in accordance with the Declaration of Helsinki. The study was part of a registered clinical trial, NCT01862497[ 7 ] registered May 24, 2013. Study Procedures Impedance Cardiography We obtained measurements 20 minutes prior to and 20 minutes following a mid-week hemodialysis treatment. Using impedance cardiography (Non-Invasive Cardiac Output Monitor [NICOM], Cheetah Medical Inc, Newton Center MA) we placed electrodes on the anterior and posterior trunk bilaterally. With the participant in the supine position, we simultaneously measured brachial artery systolic and diastolic BP and cardiac output. Three measurements were obtained at one-minute intervals, and the mean value was calculated. The total peripheral resistance (TPR) was automatically calculated by the device using the formula: mean arterial pressure (MAP) = TPR x cardiac output (CO) and expressed as dynes*seconds/cm − 5 . The TPRI was automatically calculated per body surface area using the height and weight obtained in the dialysis unit. Peridialytic Blood Pressure Measurements Immediately prior to and after the same mid-week hemodialysis treatment, dialysis unit staff measured seated systolic and diastolic BP according to dialysis unit standard procedures using sphygmomanometers attached to the hemodialysis machine. These measurements were automatically recorded in the electronic medical record. Ambulatory Blood Pressure Immediately following the mid-week treatment, we began ambulatory BP measurements with a Spacelabs 90207 machine. The first reading was obtained in the hemodialysis unit, and subsequent measurements were obtained every 30 minutes during the daytime and every hour from 10 pm to 6 am for 44 hours until the next dialysis treatment. Laboratory Data We obtained the most recent standard HD laboratory measurements from the patient’s electronic medical record that include pre-HD measurements of hemoglobin, serum phosphate, serum creatinine, serum albumin, serum PTH, serum calcium, blood urea nitrogen, and protein catabolic rate (PCR). Immediately prior to the mid-week treatment in which BP and TPRI were measured, we obtained additional plasma for measurements of endothelin-1 (ET-1) and ADMA. These samples were stored in a -80 degree C freezer and were analyzed in batch using quantitative sandwich enzyme immunoassay technique with Human Endothelin-1 Immunoassay (Quantiglo) for ET-1 and competitive enzyme linked immune-sorbent assay (Biovendor) with a microtiter plate format for ADMA. Statistical Analysis We reported descriptive statistics as mean and standard deviations for continuous variables and frequencies and percentages for categorical variables. Data determined to be a significant outlier (n = 1) was not included in final analysis. We used Pearson correlations to test whether serum phosphate are related to study outcome BP variables, other continuous variables related to BP, and laboratory measurements. When relations are significant, we then used serum phosphate as the primary predictor variable in generalized linear regression models (GLM) with the following outcome variables described in detail below (systolic and diastolic BP, pre-HD TPRI, pre-HD ET-1, pre-HD ADMA) controlling for confounders. Because the peridialytic BP measurements were related to each other for each participant, our models using BP as the outcome variable were repeated-measures linear regression analysis where the initial supine BP measurement (20 minutes pre-hemodialysis) was the primary outcome variable. We conducted separate analyses for systolic and diastolic BP. In Model 1, we controlled for age, sex, race/ethnicity, diabetes, and the remaining peri-dialytic BP measurements. We combined race and ethnicity into a binary variable, non-Hispanic White and non-white. This coarsening of race and ethnicity data into one single variable is accepted because 1) all participants were either non-Hispanic white, Hispanic white, or non-Hispanic Black and 2) both Black race and Hispanic ethnicity have been associated with higher pre-hemodialysis systolic BP[ 8 ]. In Model 2, we also included PTH and interdialytic weight gain (expressed as a percentage of weight) as independent variables. For the remaining outcome variables (pre-HD TPRI, ET-1 and ADMA), we used separate GLM with serum phosphate as the primary predictor variable. To normalize the distributions, appropriate data transformations were completed (logarithmic transformation for TPRI and ADMA; reciprocal transformation for ET-1). We controlled for age, sex, race/ethnicity, and diabetes. We used Akaike Information Criteria (AIC) and statistical significance to determine inclusion and exclusion of covariates in the final model. Our final model (model 2) also controlled for PTH and interdialytic weight gain because this had the lowest AIC, but we also explored other models that included serum calcium, albumin, and PCR. A p-value < 0.05 as set as a criterion for statistical significance. All statistical analyses were conducted using SAS 9.4 version (SAS Institute, Cary, NC). Results Participant Characteristics From a cohort of 75 patients, there were 54 with complete data available for serum phosphate, the outcomes of pre-HD BP, TPRI, serum ET-1 and ADMA, and other analyzed covariates. Thus, a final study sample size is 54. The characteristics of these 54 patients are depicted in Table 1 . Sixty-one percent of the participants were male, and 63% had diabetes. Almost all participants were receiving at least one oral phosphate binder (56% on calcium-containing binders, 41% on non-calcium-containing binders). There were 80% receiving some form of active vitamin D, and 33% receiving cinacalcet. The mean serum phosphate, calcium, and PTH levels were 1.90 (0.6) mmol/L, 2.29 (0.2) mmol/L, and 631 (700) ng/L. Table 1 Cohort Characteristics (n = 54) Age (years) 49.0 (12) African American (n, %) 33 (54) Hispanic (n, %) 16 (30) Women (n, %) 21 (39) Diabetic (n, %) 34 (63) Taking cinacalcet (n, %) 18 (33) Taking calcium containing phosphate binder (n, %) 30 (56) Taking non-calcium containing phosphate binder (n, %) 22 (41) Receiving intradialytic vitamin D agonist 43 (80) Taking angiotensin converting enzyme inhibitor (n, %) 20 (37) Taking angiotensin receptor blocker (n, %) 11 (20) Taking beta adrenergic receptor antagonist (n, %) 41 (76) Serum calcium (mmol/L) 2.29 (0.2) Serum parathyroid hormone (ng/L) 631 (700) Serum phosphate (mmol/L) 1.9 (0.6) Serum albumin (g/L) 38.2 (3) Protein catabolic rate 1.03 (0.3) Blood urea nitrogen (mmol/L) 20.2 (7.2) Serum creatinine (µmol/L) 911 (250) Serum potassium (mmol/L) 4.88 (0.6) Kt/V 1.46 (0.2) Hemoglobin (g/L) 105 (11) Treatment Time (minutes) 233 (19) Blood flow (mL/min() 409 (86) Dialysate flow (mL/min) 683 (110) Receiving 2K bath (n, %) 45 (83) Receiving 2.5 Ca bath (n, %) 53 (98) Estimated dry weight (kg) 85.8 (21) Percentage of interdialytic weight gain 3.00 (1.9) Ultrafiltration rate (mL/kg/hr) 8.00 (3.7) Pre-HD supine systolic BP (mmHg) 164 (27) Pre-HD seated systolic BP (mmHg) 158 (21) Post-HD seated systolic BP (mmhg) 142 (21) Post-HD supine systolic BP (mmHg) 152 (21) Pre-HD supine diastolic BP (mmHg) 91.5 (17) Pre-HD seated diastolic BP (mmHg); 86.1 (16) Post-HD seated diastolic BP (mmHg); 78.4 (15) Post-HD supine diastolic BP (mmHg) 86.4 (14) Mean ambulatory systolic BP (mmHg); 144 (14) Mean ambulatory diastolic BP (mmHg); 79.9 (12) Pre-HD TPRI (dynes*sec/cm − 5 /m 2 ) 3220 (850) Plasma ET-1 (pg/mL) 2.42 (1.6) Plasma ADMA (µmol/L) 0.76 (0.2) HD-Hemodialysis, BP-Blood pressure, TPRI-Total peripheral resistance index, ET-1-Endothelin-1, ADMA-Asymmetric dimethylarginine Blood Pressure Outcomes The mean pre-HD and post-HD BP in the supine and seated positions are in Table 1 . The scatterplots and trend lines showing the relationship between serum phosphate and the systolic and diastolic BP are shown in Fig. 1 . There were significant correlations between serum phosphate with systolic BP for the pre-HD supine (r = 0.3, p = .04) and seated (r = 0.4, p = .002) measurements, but not for the post-HD seated (r = 0.08, p = .6) or supine (r = 0.09, p = .5) measurements. There were significant correlations between serum phosphate and diastolic BP for the pre-HD supine (r = 0.5, p < .0001) and seated (r = 0.5, p = .0003) measurements as well as the post-HD seated (r = 0.4, p = .003) and supine (r = 0.4, p = .002) measurements. Table 2 Repeated measures linear regression analysis using pre-hemodialysis supine blood pressure as the primary outcome variable (n=54) Systolic Blood Pressure Model 1 Model 2 Estimate (SE) p-value Estimate (SE) p-value Intercept 150.0 (16) <.0001 147 (17) <.0001 Phosphate (mg/dL) 3.82 (2.0) .06 3.82 (2.0) .06 Parathyroid hormone (ng/L) - - 0.002 (0.003) .9 Interdialytic Weight Gain as percentage of body weight - - 0.78 (1.0) .5 Diastolic Blood Pressure Intercept 84.3 (9.7) <.0001 85.4 (10) <.0001 Phosphate (mg/dL) 4.22 (1.1) .0002 4.31 (6.7) .0002 Parathyroid Hormone (ng/L) - - -0.002 (0.002) .4 Interdialytic Weight Gain as percentage of body weight - - 0.16 (0.7) .8 While not present, all models also controlled for age, sex, race, ethnicity, diabetes, and the subsequent BP measurements (pre and post-HD seated, and post-HD supine) Vasoconstriction and Markers of Endothelial Cell Dysfunction The Pearson correlation coefficients for serum phosphate with pre-HD TPRI, ET-1, and ADMA were 0.3 (p = .01), 0.4 (p = .007), and 0.3 (p = .04), respectively. Table 3 shows that there were independent associations between serum phosphate and both higher TPRI and ET-1 (negative regression coefficient in the context of reciprocal transformation) in models that included demographic variables, PTH and weight gain, while there was no serum phosphate association with ADMA. Parathyroid hormone (PTH) was positively correlated with ADMA (r = 0.3, p = .01) in univariate Pearson correlation analysis, but its statistical significance was slightly attenuated when controlled for other covariates in our regression analysis (p = .06). In addition, we explored other models that including albumin, PCR, or calcium (data not shown) as additional covariates and found the associations between phosphate and all outcomes remained unchanged. Thus, the final model did not include these covariates guided by AIC and statistical significance. Table 3 Linear regression models showing associations between serum phosphate with various pre-HD outcomes Total peripheral resistance index (log transformation) Endothelin-1 (reciprocal transformation) Asymmetric dimethylarginine (log transformation) Estimate ( \(\pm SE)\) p-value Estimate ( \(\pm SE)\) p-value Estimate ( \(\pm SE)\) p-value Serum Phosphate (mg/dL) 0.05 (0.02) .005 -0.03 (0.02) .047 0.02 (0.02) .3 Models also controlled for age, sex, diabetes, Black race or Hispanic ethnicity, Parathyroid Hormone (PTH), and percentage of interdialytic weight gain Discussion The principal finding of this study was that serum phosphate was associated with high HD-unit BP, vasoconstriction, and markers of ECD. Phosphate was independently associated with higher pre-HD diastolic BP, TPRI, and ET-1 while controlling for numerous demographic variables. ADMA was associated with both phosphate and PTH in univariate analyses, but there appear to be other confounding variables behind this relationship. Overall, these findings demonstrate a novel relationship between MBD and cardiovascular disease in ESRD patients that may be independent of vascular calcification. Serum phosphate is associated with increased morbidity and mortality in CKD patients[ 1 , 9 ], though it is unknown whether BP is directly involved in this relationship. Intervention studies in both animals and healthy humans have demonstrated increases in BP following extended periods of high dietary phosphate intake[ 10 , 11 ]. One observational study in pre-ESRD CKD patients showed a moderate correlation between serum phosphate and systolic BP which was predominantly found in the patients with diabetes (n = 30), but there was not adjustment for any other variables[ 12 ]. Another study in ESRD patients found that diastolic, but not systolic, BP (both measured pre-HD) was higher in patients in the highest tertile of serum phosphate[ 13 ]. Our study is novel in that we controlled for numerous demographic variables that have been associated with high pre-HD BP, we analyzed phosphate as a continuous variable, and we included analyses of vasoconstriction measurements and markers of ECD[ 8 , 14 ]. Some of the proposed mechanisms to explain a relationship between phosphate and BP include increased arterial stiffness, increased renin-angiotensin-aldosterone system (RAAS) activity, and increased sympathetic nervous system (SNS) activity [ 10 , 11 , 15 , 16 ]. The negative consequences of increased arterial stiffness include increased central aortic BP (which can contribute to left ventricular hypertrophy) and widened pulse pressure (which can contribute to coronary hypoperfusion.) Unfortunately, the structural changes from vascular calcification may persist even after serum phosphate is acutely brought under control. Our findings of the particularly strong association between phosphate and diastolic BP seem to deviate from the phenotype of isolated systolic hypertension that is often seen with increased arterial stiffness, which suggests that another mechanism may be responsible. As this was a post-hoc analysis from a previously conducted study, we did not have any assessment of RAAS or SNS activity to further evaluate possible explanations for relationship between phosphate and vasoconstriction. However, a large percentage of patients were receiving RAAS inhibiting drugs and/or beta adrenergic receptor antagonists. Another mechanism proposed to explain the relationship between phosphate and cardiovascular disease is ECD. In an in vitro study, rat aortic ring cells exposed to a high phosphate medium showed significant decrease in dilation compared to those exposed to lower phosphate-containing medium[ 2 ]. The same investigators found that healthy humans ingesting a high phosphate meal experienced acute reduction in flow mediated vasodilation post-prandially which was inversely correlated with the serum phosphate level[ 2 ]. This study also reported an increase in PTH following phosphate ingestion, which was not accounted for in the analysis. In a community based population study, where only 7% had estimated glomerular filtration rates < 60 mL/min/1.73m 2 , the investigators found an association between serum phosphate and microvascular dysfunction assessed with skin capillaroscopy[ 17 ]. Surprisingly, a cross sectional study in patients undergoing hemodialysis fistula placement found that a U-shaped curve defined the relationship between serum phosphate and FMD independent of BP, race, or presence of diabetes[ 18 ]. Parathyroid hormone and other variables related to MBD and nutrition were not taken into consideration, and roughly one third of patients in that study had pre-dialysis CKD. Of note, one clinical trial found that suppression of PTH with intravenous vitamin D analogues improved FMD in CKD patients, but this effect was blunted among patients with persistently high phosphate levels[ 19 ]. Collectively, these demonstrate that phosphate and/or additional MBD factors adversely influence ECD. We were able to evaluate some relationship between phosphate and ECD by including analysis of plasma ET-1 and ADMA. We found that phosphate was independently associated with ET-1, an endothelial cell derived vasoconstrictor. A phosphate-induced increase in ET-1 has been previously observed in both human endothelial cells and rat models of CKD[ 20 ]. Our novel finding in humans warrants longitudinal research to determine if improving phosphate control lowers ET-1 and possibly TPRI and BP. We also found that serum phosphate and PTH were associated with ADMA, and endogenous inhibitor of nitric oxide synthase that is associated with cardiovascular morbidity and mortality in HD patients[ 5 ]. This is consistent with the findings of Coen et al. revealing phosphate and PTH are individually associated with ADMA in ESRD patients[ 21 ]. Overall, our findings demonstrate a significant relationship between serum phosphate, vasoconstriction, and ECD in HD patients. It will ultimately need to be determined whether improvement in serum phosphate alone would be sufficient to improve ECD and lower BP in this population. One small randomized trial in CKD IV patients found that treatment with the phosphate binder sevelamer improved FMD, but use of a calcium-containing binder calcium acetate did not[ 22 ]. Improvement in FMD was strongly associated with levels of a calcification inhibitor, fetuin A, bringing forth an additional player in the interaction between MBD and vascular health. In that study, the phosphate remained high after treatment and many patients with comorbidities found in CKD and HD patients (diabetes, coronary artery disease, smoking, and use of renin-angiotensin-aldosterone system inhibitors or statins) were excluded. Another trial in a more heterogeneous CKD population found no significant changes or between-group differences in pulse wave velocity, coronary artery calcium score, or reactive hyperemia index (to assess ECD) in the participants randomized to lanthanum, calcium acetate, or low phosphate diet[ 23 ]. These studies highlight the need for further research that comprehensively takes into account the numerous mediators of MBD on vascular function and BP. Limitations to our study include its relatively small size and the inability to draw conclusions about causality due its observational nature. Furthermore, we used ET-1 and ADMA as biomarkers for ECD. Because this was a retrospective analysis, we did not have alternative measurements such as FMD available. Additionally, the serum phosphate and other HD lab measurements were obtained in the context of routine clinical care and did not occur on the exact same date as our BP and TPRI measurements. However, we used the most recent measurements of phosphate preceding our measurements that usually occurred within a 1–2 week period. Our study had numerous strengths related to the variables that we ascertained and controlled for in the analysis to establish the presence of an independent association. Conclusion In conclusion, we found that there is a positive association between serum phosphate and peri-dialytic BP. The association with diastolic BP was particularly strong and was independent of PTH, interdialytic weight gain and other variables. We found that phosphate was also related to pre-HD vasoconstriction and ECD markers, although the association with ADMA was not fully independent of other factors. These findings require further investigation to determine the hemodynamic benefits of aggressive phosphate lowering in ESRD and even possibly in pre-ESRD chronic kidney disease. They also introduce the possibility of more targeted approaches to BP management among patients with refractory hyperphosphatemia. Such research will require comprehensive assessment of the numerous mediators of MBD. Abbreviations MBD Mineral Bone Disease ESRD End stage renal disease HD Hemodialysis PTH Parathyroid hormone ECD Endothelial cell dysfunction ADMA Asymmetric dimethyarginine BP Blood Pressure TPRI Total peripheral resistance index NICOM Non-invasive cardiac output monitor TPR Total peripheral resistance MAP Mean arterial pressure CO Cardiac output PCR Protein catabolic rate ET-1 Endothelin-1 GLM Generalized linear regression models AIC Akaike Information Criteria RAAS Renin angiotensin aldosterone system SNS Sympathetic nervous system Declarations Statement of Ethics: The study protocol was reviewed and approved by the University of Texas Southwestern Medical Center Institutional Review Board approved the protocol (STU 052012-029 first approved 8/9/2012). All participants provided written informed consent. All procedures were in accordance with the Declaration of Helsinki. The study was part of a registered clinical trial, NCT01862497 (May 24, 2013). Consent for publication: not applicable Availability of Data and materials: The datasets analyzed during the current study are available from the corresponding author on reasonable request. Competing Interests: Dr. Van Buren serves on the Editorial Board for BMC Nephrology, but there are no significant financial or non-financial competing interests. Funding Sources: Funding for this study came from NIDDK 1K23DK096007-01A1 (PVB) and VA Merit CX002009-1 as well as support from the University of Texas Southwestern O’Brien Kidney Research Core (NIH grant P30DK079328). Dr. Van Buren also receives institutional support from UT Southwestern as a Dedman Family Scholar in Clinical Care. Author Contributions: JJ: Writing-review and editing; presentation at ASN meeting HJS: Formal Data analysis, writing review and editing HN: Formal Data analysis, writing review and editing JP, KS, SS: Investigation; Writing-review and editing PVB: Conceptualization, Investigation, Project Administration, Data collection, Writing-original draft; review and editing Acknowledgements: Data from this study was presented as a virtual poster at the American Society of Nephrology Kidney Week Meeting (November 2021). References Kalantar-Zadeh K, Kuwae N, Regidor D et al. Survical predictability of time-varying indicators of bone disease in maintenance hemodialysis patients. Kidney International 2006; 70:771–780. Shuto E, Taketani Y, Tanaka R et al. Dietary Phosphorus Acutely Impairs Endothelial Function. J Am Soc Nephrol 2009; 20:1504–1512. Agarwal R, Nissenson A, Batlle D et al. Prevalence, Treatment, and Control of Hypertension in Chronic Hemodialysis Patients in the United States. 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Nutrition, Metabolism, and Cardiovascular Disease 2016; 26:581–589. Olmos G, Martinez-Miguel P, Alcalde-Estevez E et al. Hyperphosphatemia induces senescence in human endothelial cells by increasing endothelin-1 production. Aging Cell 2017; 16:1300–1312. Coen G, Mantella D, Sardella D et al. Asymmetric dimethylarginine, vascular calcifications and parathyroid hormone serum levels in hemodialysis patients. Journal of Nephrology 2009; 22:616–622. Caglar K, Yilmaz M, Saglam M et al. Short-Term Treatment with Sevelamer Increases Serum Fetuin-A Concentration and Improves Endothelial Dysfunction in Chronic Kidney Disease 4 Patients. Clin J Am Soc Nephrol 2008; 3:61–68. Kovesdy C, Lu J, Wall B et al. Changes with Lanthanum Carbonate, Calcium Acetate, and Phosphorus Restriction in CKD: A Randomized Controlled Trial. Kidney Int Rep 2018; 3:897–904. Additional Declarations Competing interest reported. Dr. Van Buren serves on the Editorial Board for BMC Nephrology, but there are no significant financial or non-financial competing interests. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 30 May, 2022 Reviews received at journal 27 May, 2022 Reviewers agreed at journal 18 May, 2022 Reviews received at journal 18 Apr, 2022 Reviewers agreed at journal 12 Apr, 2022 Reviewers invited by journal 09 Apr, 2022 Editor assigned by journal 09 Apr, 2022 Editor invited by journal 08 Apr, 2022 Submission checks completed at journal 08 Apr, 2022 First submitted to journal 04 Apr, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1523519","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":97262568,"identity":"71eec132-d8a1-45e3-8fc2-a50c4040f6c9","order_by":0,"name":"Jinwoo Jung","email":"","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jinwoo","middleName":"","lastName":"Jung","suffix":""},{"id":97262569,"identity":"81a5a625-7198-4974-af33-8e3f99a01869","order_by":1,"name":"Haekyung Jeon-Slaughter","email":"","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Haekyung","middleName":"","lastName":"Jeon-Slaughter","suffix":""},{"id":97262570,"identity":"2cc38576-0dd7-429c-ad28-04ed0d363279","order_by":2,"name":"Hang Nguyen","email":"","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hang","middleName":"","lastName":"Nguyen","suffix":""},{"id":97262571,"identity":"e1e978b9-a1e7-4fba-acbf-96f4dd8d8e6f","order_by":3,"name":"Jiten Patel","email":"","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jiten","middleName":"","lastName":"Patel","suffix":""},{"id":97262572,"identity":"f3da6f82-8e45-4fd6-8c0f-18fd6f9fc53c","order_by":4,"name":"Kamalanathan K. Sambandam","email":"","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kamalanathan","middleName":"K.","lastName":"Sambandam","suffix":""},{"id":97262573,"identity":"420a0530-e524-46c4-89e2-37a072651a9f","order_by":5,"name":"Shani Shastri","email":"","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shani","middleName":"","lastName":"Shastri","suffix":""},{"id":97262574,"identity":"4ac74d0b-58c3-4021-9523-9f35fa4880fa","order_by":6,"name":"Peter Noel Buren","email":"data:image/png;base64,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","orcid":"","institution":"University of Texas Southwestern Medical Center","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Peter","middleName":"Noel","lastName":"Buren","suffix":""}],"badges":[],"createdAt":"2022-04-04 22:44:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1523519/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1523519/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":20205104,"identity":"23ba8f29-b0f3-4059-a5e1-343386622f50","added_by":"auto","created_at":"2022-04-11 17:00:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29324,"visible":true,"origin":"","legend":"\u003cp\u003eScatterplot and trendlines for comparison of systolic (1A) and diastolic (1B) blood pressure vs serum phosphate\u003c/p\u003e\u003cp\u003eA shows the scatterplots and trend lines for systolic BP (y-axis) and serum phosphate (x-axis).\u0026nbsp;The systolic BP measurements include supine measurements 20 minutes before dialysis in red (r=0.3, p=.04), seated measurements immediately before HD in blue (r=0.4, p=.002), seated measurements immediately after HD in gray (r=0.08, p=.6), and supine measurements 20 minutes after dialysis in green (r=0.09, p=.5).\u003c/p\u003e\u003cp\u003eB shows the scatterplots and trend lines for diastolic BP (y-axis) and serum phosphate (x-axis).\u0026nbsp;The diastolic BP measurements include supine measurements 20 minutes before dialysis in red (r=0.5, p\u0026lt;.0001), seated measurements immediately before HD in blue (r=0.5, p=.0003), seated measurements immediately after HD in gray (r=0.4, p=0.003), and supine measurements 20 minutes after dialysis in green (r=0.4, p=.002).\u003c/p\u003e","description":"","filename":"OnlineFIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-1523519/v1/ce5171a4428dd56ad0be9b12.png"},{"id":20205105,"identity":"eb909051-edab-4d95-968e-6dd3199abf8f","added_by":"auto","created_at":"2022-04-11 17:00:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":416878,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1523519/v1/56310ec4-2127-4062-b752-ecba2b93356a.pdf"}],"financialInterests":"Competing interest reported. Dr. Van Buren serves on the Editorial Board for BMC Nephrology, but there are no significant financial or non-financial competing interests.","formattedTitle":"Hyperphosphatemia and its Relationship with Blood Pressure, Vasoconstriction, and Endothelial Cell Dysfunction in Hypertensive Hemodialysis Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMineral bone disease (MBD) is a non-traditional cardiovascular disease risk factor that contributes to the high mortality rate among end stage renal disease (ESRD) patients on hemodialysis (HD). Hyperphosphatemia and the related increases in parathyroid hormone (PTH) are each independently associated with mortality in this population[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Chronically elevated serum phosphate contributes to structural changes in blood vessels including vascular calcification, but it is also likely to be associated with other \u003cem\u003efunctional\u003c/em\u003e abnormalities of the blood vessels that may be more easily reversible.\u003c/p\u003e \u003cp\u003eRecent experimental evidence shows that acute increases in phosphate both in vitro and in healthy individuals can induce acute endothelial cell dysfunction (ECD)[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The most common clinical scenario where hyperphosphatemia is observed is in advanced chronic kidney disease, especially ESRD. Compared to healthy individuals, ESRD patients also have a much higher risk of hypertension and more severe ECD[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] with ECD markers such as asymmetric dimethylarginine (ADMA) being predictive of increased mortality [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Despite this, there is little data on the relationship between phosphate and adverse cardiovascular consequences beyond vascular calcification. A better understanding of these relationships is needed to provide a more comprehensive approach to addressing mortality risk reduction in ESRD patients.\u003c/p\u003e \u003cp\u003eWe hypothesized that elevated serum phosphate would be independently associated with blood pressure (BP), as well as measurements of vasoconstriction and markers of ECD in hypertensive hemodialysis patients. We analyzed these associations within a cohort of patients receiving maintenance HD.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Participants\u003c/h2\u003e \u003cp\u003eWe used previously collected data from a prospective cohort of hypertensive ESRD patients on maintenance HD to conduct a cross-sectional study of some of the baseline measurements. The intent of the primary study was to determine the association between intradialytic changes in total peripheral resistance index (TPRI) with ambulatory BP in hypertensive hemodialysis patients. Study inclusion criteria for the original study were 1) age\u0026thinsp;\u0026gt;\u0026thinsp;18 years, 2) HD vintage\u0026thinsp;\u0026gt;\u0026thinsp;1 month, and 3) peri-dialytic hypertension defined as pre-HD systolic BP\u0026thinsp;\u0026gt;\u0026thinsp;140 mmHg or post-HD systolic BP\u0026thinsp;\u0026gt;\u0026thinsp;130 mmHg[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Exclusion criteria were defined by the presence of a cardiac defibrillator or pacemaker, arm or leg amputation, coronary artery stent, implanted metallic prosthesis, pregnancy, or the inability to achieve estimated dry weight defined by the nephrologist providing the clinical care. The first 36 participants enrolled had either recurrent increases in systolic BP from pre to post-HD\u0026thinsp;\u0026gt;\u0026thinsp;10 mmHg (n\u0026thinsp;=\u0026thinsp;18) or recurrent decreases in systolic BP from pre to post-HD\u0026thinsp;\u0026gt;\u0026thinsp;10 mmHg (n\u0026thinsp;=\u0026thinsp;18). Subsequent enrollment did not require any specific intradialytic BP pattern as long as other inclusion and exclusion criteria were fulfilled. The University of Texas Southwestern Medical Center Institutional Review Board approved the protocol, and all procedures were in accordance with the Declaration of Helsinki. The study was part of a registered clinical trial, NCT01862497[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] registered May 24, 2013.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Procedures\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eImpedance Cardiography\u003c/h2\u003e \u003cp\u003eWe obtained measurements 20 minutes prior to and 20 minutes following a mid-week hemodialysis treatment. Using impedance cardiography (Non-Invasive Cardiac Output Monitor [NICOM], Cheetah Medical Inc, Newton Center MA) we placed electrodes on the anterior and posterior trunk bilaterally. With the participant in the supine position, we simultaneously measured brachial artery systolic and diastolic BP and cardiac output. Three measurements were obtained at one-minute intervals, and the mean value was calculated. The total peripheral resistance (TPR) was automatically calculated by the device using the formula: mean arterial pressure (MAP)\u0026thinsp;=\u0026thinsp;TPR x cardiac output (CO) and expressed as dynes*seconds/cm\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e. The TPRI was automatically calculated per body surface area using the height and weight obtained in the dialysis unit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003ePeridialytic Blood Pressure Measurements\u003c/h2\u003e \u003cp\u003eImmediately prior to and after the same mid-week hemodialysis treatment, dialysis unit staff measured seated systolic and diastolic BP according to dialysis unit standard procedures using sphygmomanometers attached to the hemodialysis machine. These measurements were automatically recorded in the electronic medical record.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eAmbulatory Blood Pressure\u003c/h2\u003e \u003cp\u003eImmediately following the mid-week treatment, we began ambulatory BP measurements with a Spacelabs 90207 machine. The first reading was obtained in the hemodialysis unit, and subsequent measurements were obtained every 30 minutes during the daytime and every hour from 10 pm to 6 am for 44 hours until the next dialysis treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003eLaboratory Data\u003c/h2\u003e \u003cp\u003eWe obtained the most recent standard HD laboratory measurements from the patient\u0026rsquo;s electronic medical record that include pre-HD measurements of hemoglobin, serum phosphate, serum creatinine, serum albumin, serum PTH, serum calcium, blood urea nitrogen, and protein catabolic rate (PCR). Immediately prior to the mid-week treatment in which BP and TPRI were measured, we obtained additional plasma for measurements of endothelin-1 (ET-1) and ADMA. These samples were stored in a -80 degree C freezer and were analyzed in batch using quantitative sandwich enzyme immunoassay technique with Human Endothelin-1 Immunoassay (Quantiglo) for ET-1 and competitive enzyme linked immune-sorbent assay (Biovendor) with a microtiter plate format for ADMA.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eWe reported descriptive statistics as mean and standard deviations for continuous variables and frequencies and percentages for categorical variables. Data determined to be a significant outlier (n\u0026thinsp;=\u0026thinsp;1) was not included in final analysis.\u003c/p\u003e \u003cp\u003eWe used Pearson correlations to test whether serum phosphate are related to study outcome BP variables, other continuous variables related to BP, and laboratory measurements. When relations are significant, we then used serum phosphate as the primary predictor variable in generalized linear regression models (GLM) with the following outcome variables described in detail below (systolic and diastolic BP, pre-HD TPRI, pre-HD ET-1, pre-HD ADMA) controlling for confounders.\u003c/p\u003e \u003cp\u003eBecause the peridialytic BP measurements were related to each other for each participant, our models using BP as the outcome variable were repeated-measures linear regression analysis where the initial supine BP measurement (20 minutes pre-hemodialysis) was the primary outcome variable. We conducted separate analyses for systolic and diastolic BP. In Model 1, we controlled for age, sex, race/ethnicity, diabetes, and the remaining peri-dialytic BP measurements. We combined race and ethnicity into a binary variable, non-Hispanic White and non-white. This coarsening of race and ethnicity data into one single variable is accepted because 1) all participants were either non-Hispanic white, Hispanic white, or non-Hispanic Black and 2) both Black race and Hispanic ethnicity have been associated with higher pre-hemodialysis systolic BP[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In Model 2, we also included PTH and interdialytic weight gain (expressed as a percentage of weight) as independent variables.\u003c/p\u003e \u003cp\u003eFor the remaining outcome variables (pre-HD TPRI, ET-1 and ADMA), we used separate GLM with serum phosphate as the primary predictor variable. To normalize the distributions, appropriate data transformations were completed (logarithmic transformation for TPRI and ADMA; reciprocal transformation for ET-1). We controlled for age, sex, race/ethnicity, and diabetes. We used Akaike Information Criteria (AIC) and statistical significance to determine inclusion and exclusion of covariates in the final model. Our final model (model 2) also controlled for PTH and interdialytic weight gain because this had the lowest AIC, but we also explored other models that included serum calcium, albumin, and PCR. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as set as a criterion for statistical significance. All statistical analyses were conducted using SAS 9.4 version (SAS Institute, Cary, NC).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eParticipant Characteristics\u003c/h2\u003e\n\u003cp\u003eFrom a cohort of 75 patients, there were 54 with complete data available for serum phosphate, the outcomes of pre-HD BP, TPRI, serum ET-1 and ADMA, and other analyzed covariates. Thus, a final study sample size is 54. The characteristics of these 54 patients are depicted in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Sixty-one percent of the participants were male, and 63% had diabetes. Almost all participants were receiving at least one oral phosphate binder (56% on calcium-containing binders, 41% on non-calcium-containing binders). There were 80% receiving some form of active vitamin D, and 33% receiving cinacalcet. The mean serum phosphate, calcium, and PTH levels were 1.90 (0.6) mmol/L, 2.29 (0.2) mmol/L, and 631 (700) ng/L.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCohort Characteristics (n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e49.0 (12)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAfrican American (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e33 (54)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHispanic (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16 (30)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWomen (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21 (39)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetic (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34 (63)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking cinacalcet (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18 (33)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking calcium containing phosphate binder (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30 (56)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking non-calcium containing phosphate binder (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22 (41)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReceiving intradialytic vitamin D agonist\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43 (80)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking angiotensin converting enzyme inhibitor (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20 (37)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking angiotensin receptor blocker (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11 (20)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTaking beta adrenergic receptor antagonist (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41 (76)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum calcium (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.29 (0.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum parathyroid hormone (ng/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e631 (700)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum phosphate (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.9 (0.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum albumin (g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38.2 (3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eProtein catabolic rate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.03 (0.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlood urea nitrogen (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.2 (7.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum creatinine (\u0026micro;mol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e911 (250)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum potassium (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.88 (0.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKt/V\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.46 (0.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105 (11)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTreatment Time (minutes)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e233 (19)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlood flow (mL/min()\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e409 (86)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDialysate flow (mL/min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e683 (110)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReceiving 2K bath (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45 (83)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eReceiving 2.5 Ca bath (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53 (98)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEstimated dry weight (kg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85.8 (21)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePercentage of interdialytic weight gain\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.00 (1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUltrafiltration rate (mL/kg/hr)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.00 (3.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-HD supine systolic BP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e164 (27)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-HD seated systolic BP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e158 (21)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePost-HD seated systolic BP (mmhg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e142 (21)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePost-HD supine systolic BP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e152 (21)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-HD supine diastolic BP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91.5 (17)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-HD seated diastolic BP (mmHg);\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e86.1 (16)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePost-HD seated diastolic BP (mmHg);\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e78.4 (15)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePost-HD supine diastolic BP (mmHg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e86.4 (14)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean ambulatory systolic BP (mmHg);\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e144 (14)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMean ambulatory diastolic BP (mmHg);\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e79.9 (12)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-HD TPRI (dynes*sec/cm\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3220 (850)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePlasma ET-1 (pg/mL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.42 (1.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePlasma ADMA (\u0026micro;mol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.76 (0.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eHD-Hemodialysis, BP-Blood pressure, TPRI-Total peripheral resistance index, ET-1-Endothelin-1, ADMA-Asymmetric dimethylarginine\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n\u003ch2\u003eBlood Pressure Outcomes\u003c/h2\u003e\n\u003cp\u003eThe mean pre-HD and post-HD BP in the supine and seated positions are in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The scatterplots and trend lines showing the relationship between serum phosphate and the systolic and diastolic BP are shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. There were significant correlations between serum phosphate with systolic BP for the pre-HD supine (r\u0026thinsp;=\u0026thinsp;0.3, p\u0026thinsp;=\u0026thinsp;.04) and seated (r\u0026thinsp;=\u0026thinsp;0.4, p\u0026thinsp;=\u0026thinsp;.002) measurements, but not for the post-HD seated (r\u0026thinsp;=\u0026thinsp;0.08, p\u0026thinsp;=\u0026thinsp;.6) or supine (r\u0026thinsp;=\u0026thinsp;0.09, p\u0026thinsp;=\u0026thinsp;.5) measurements. There were significant correlations between serum phosphate and diastolic BP for the pre-HD supine (r\u0026thinsp;=\u0026thinsp;0.5, p\u0026thinsp;\u0026lt;\u0026thinsp;.0001) and seated (r\u0026thinsp;=\u0026thinsp;0.5, p\u0026thinsp;=\u0026thinsp;.0003) measurements as well as the post-HD seated (r\u0026thinsp;=\u0026thinsp;0.4, p\u0026thinsp;=\u0026thinsp;.003) and supine (r\u0026thinsp;=\u0026thinsp;0.4, p\u0026thinsp;=\u0026thinsp;.002) measurements.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2 Repeated measures linear regression analysis using pre-hemodialysis supine blood pressure as the primary outcome variable (n=54)\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"618\"\u003e\n\u003cp\u003e\u003cstrong\u003eSystolic Blood Pressure\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"174\"\u003e\n\u003cp\u003eModel 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"222\"\u003e\n\u003cp\u003eModel 2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003eEstimate (SE)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003eEstimate (SE)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003eIntercept\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e150.0 (16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e147 (17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003ePhosphate (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e3.82 (2.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e3.82 (2.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003eParathyroid hormone (ng/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e0.002 (0.003)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003eInterdialytic Weight Gain as percentage of body weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e0.78 (1.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"618\"\u003e\n\u003cp\u003e\u003cstrong\u003eDiastolic Blood Pressure\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003eIntercept\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e84.3 (9.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e85.4 (10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003ePhosphate (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e4.22 (1.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e.0002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e4.31 (6.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e.0002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003eParathyroid Hormone (ng/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e-0.002 (0.002)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"222\"\u003e\n\u003cp\u003eInterdialytic Weight Gain as percentage of body weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"108\"\u003e\n\u003cp\u003e0.16 (0.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"114\"\u003e\n\u003cp\u003e.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"618\"\u003e\n\u003cp\u003eWhile not present, all models also controlled for age, sex, race, ethnicity, diabetes, and the subsequent BP measurements (pre and post-HD seated, and post-HD supine)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n\u003ch2\u003eVasoconstriction and Markers of Endothelial Cell Dysfunction\u003c/h2\u003e\n\u003cp\u003eThe Pearson correlation coefficients for serum phosphate with pre-HD TPRI, ET-1, and ADMA were 0.3 (p\u0026thinsp;=\u0026thinsp;.01), 0.4 (p\u0026thinsp;=\u0026thinsp;.007), and 0.3 (p\u0026thinsp;=\u0026thinsp;.04), respectively. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows that there were independent associations between serum phosphate and both higher TPRI and ET-1 (negative regression coefficient in the context of reciprocal transformation) in models that included demographic variables, PTH and weight gain, while there was no serum phosphate association with ADMA. Parathyroid hormone (PTH) was positively correlated with ADMA (r\u0026thinsp;=\u0026thinsp;0.3, p\u0026thinsp;=\u0026thinsp;.01) in univariate Pearson correlation analysis, but its statistical significance was slightly attenuated when controlled for other covariates in our regression analysis (p\u0026thinsp;=\u0026thinsp;.06). In addition, we explored other models that including albumin, PCR, or calcium (data not shown) as additional covariates and found the associations between phosphate and all outcomes remained unchanged. Thus, the final model did not include these covariates guided by AIC and statistical significance.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eLinear regression models showing associations between serum phosphate with various pre-HD outcomes\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eTotal peripheral resistance index (log transformation)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eEndothelin-1 (reciprocal transformation)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAsymmetric dimethylarginine (log transformation)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEstimate (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm SE)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEstimate (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm SE)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEstimate (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\pm SE)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSerum Phosphate (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.05 (0.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.03 (0.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.047\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02 (0.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\" align=\"left\"\u003e\n\u003cp\u003eModels also controlled for age, sex, diabetes, Black race or Hispanic ethnicity, Parathyroid Hormone (PTH), and percentage of interdialytic weight gain\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe principal finding of this study was that serum phosphate was associated with high HD-unit BP, vasoconstriction, and markers of ECD. Phosphate was independently associated with higher pre-HD diastolic BP, TPRI, and ET-1 while controlling for numerous demographic variables. ADMA was associated with both phosphate and PTH in univariate analyses, but there appear to be other confounding variables behind this relationship. Overall, these findings demonstrate a novel relationship between MBD and cardiovascular disease in ESRD patients that may be independent of vascular calcification.\u003c/p\u003e \u003cp\u003eSerum phosphate is associated with increased morbidity and mortality in CKD patients[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], though it is unknown whether BP is directly involved in this relationship. Intervention studies in both animals and healthy humans have demonstrated increases in BP following extended periods of high dietary phosphate intake[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. One observational study in pre-ESRD CKD patients showed a moderate correlation between serum phosphate and systolic BP which was predominantly found in the patients with diabetes (n\u0026thinsp;=\u0026thinsp;30), but there was not adjustment for any other variables[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Another study in ESRD patients found that diastolic, but not systolic, BP (both measured pre-HD) was higher in patients in the highest tertile of serum phosphate[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Our study is novel in that we controlled for numerous demographic variables that have been associated with high pre-HD BP, we analyzed phosphate as a continuous variable, and we included analyses of vasoconstriction measurements and markers of ECD[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome of the proposed mechanisms to explain a relationship between phosphate and BP include increased arterial stiffness, increased renin-angiotensin-aldosterone system (RAAS) activity, and increased sympathetic nervous system (SNS) activity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The negative consequences of increased arterial stiffness include increased central aortic BP (which can contribute to left ventricular hypertrophy) and widened pulse pressure (which can contribute to coronary hypoperfusion.) Unfortunately, the structural changes from vascular calcification may persist even after serum phosphate is acutely brought under control. Our findings of the particularly strong association between phosphate and \u003cem\u003ediastolic\u003c/em\u003e BP seem to deviate from the phenotype of isolated systolic hypertension that is often seen with increased arterial stiffness, which suggests that another mechanism may be responsible. As this was a post-hoc analysis from a previously conducted study, we did not have any assessment of RAAS or SNS activity to further evaluate possible explanations for relationship between phosphate and vasoconstriction. However, a large percentage of patients were receiving RAAS inhibiting drugs and/or beta adrenergic receptor antagonists.\u003c/p\u003e \u003cp\u003eAnother mechanism proposed to explain the relationship between phosphate and cardiovascular disease is ECD. In an \u003cem\u003ein vitro\u003c/em\u003e study, rat aortic ring cells exposed to a high phosphate medium showed significant decrease in dilation compared to those exposed to lower phosphate-containing medium[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The same investigators found that healthy humans ingesting a high phosphate meal experienced acute reduction in flow mediated vasodilation post-prandially which was inversely correlated with the serum phosphate level[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This study also reported an increase in PTH following phosphate ingestion, which was not accounted for in the analysis. In a community based population study, where only 7% had estimated glomerular filtration rates\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, the investigators found an association between serum phosphate and microvascular dysfunction assessed with skin capillaroscopy[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Surprisingly, a cross sectional study in patients undergoing hemodialysis fistula placement found that a U-shaped curve defined the relationship between serum phosphate and FMD independent of BP, race, or presence of diabetes[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Parathyroid hormone and other variables related to MBD and nutrition were not taken into consideration, and roughly one third of patients in that study had pre-dialysis CKD. Of note, one clinical trial found that suppression of PTH with intravenous vitamin D analogues improved FMD in CKD patients, but this effect was blunted among patients with persistently high phosphate levels[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Collectively, these demonstrate that phosphate and/or additional MBD factors adversely influence ECD.\u003c/p\u003e \u003cp\u003eWe were able to evaluate some relationship between phosphate and ECD by including analysis of plasma ET-1 and ADMA. We found that phosphate was independently associated with ET-1, an endothelial cell derived vasoconstrictor. A phosphate-induced increase in ET-1 has been previously observed in both human endothelial cells and rat models of CKD[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our novel finding in humans warrants longitudinal research to determine if improving phosphate control lowers ET-1 and possibly TPRI and BP. We also found that serum phosphate and PTH were associated with ADMA, and endogenous inhibitor of nitric oxide synthase that is associated with cardiovascular morbidity and mortality in HD patients[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This is consistent with the findings of Coen et al. revealing phosphate and PTH are individually associated with ADMA in ESRD patients[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverall, our findings demonstrate a significant relationship between serum phosphate, vasoconstriction, and ECD in HD patients. It will ultimately need to be determined whether improvement in serum phosphate alone would be sufficient to improve ECD and lower BP in this population. One small randomized trial in CKD IV patients found that treatment with the phosphate binder sevelamer improved FMD, but use of a calcium-containing binder calcium acetate did not[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Improvement in FMD was strongly associated with levels of a calcification inhibitor, fetuin A, bringing forth an additional player in the interaction between MBD and vascular health. In that study, the phosphate remained high after treatment and many patients with comorbidities found in CKD and HD patients (diabetes, coronary artery disease, smoking, and use of renin-angiotensin-aldosterone system inhibitors or statins) were excluded. Another trial in a more heterogeneous CKD population found no significant changes or between-group differences in pulse wave velocity, coronary artery calcium score, or reactive hyperemia index (to assess ECD) in the participants randomized to lanthanum, calcium acetate, or low phosphate diet[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These studies highlight the need for further research that comprehensively takes into account the numerous mediators of MBD on vascular function and BP.\u003c/p\u003e \u003cp\u003eLimitations to our study include its relatively small size and the inability to draw conclusions about causality due its observational nature. Furthermore, we used ET-1 and ADMA as biomarkers for ECD. Because this was a retrospective analysis, we did not have alternative measurements such as FMD available. Additionally, the serum phosphate and other HD lab measurements were obtained in the context of routine clinical care and did not occur on the exact same date as our BP and TPRI measurements. However, we used the most recent measurements of phosphate preceding our measurements that usually occurred within a 1\u0026ndash;2 week period. Our study had numerous strengths related to the variables that we ascertained and controlled for in the analysis to establish the presence of an independent association.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, we found that there is a positive association between serum phosphate and peri-dialytic BP. The association with diastolic BP was particularly strong and was independent of PTH, interdialytic weight gain and other variables. We found that phosphate was also related to pre-HD vasoconstriction and ECD markers, although the association with ADMA was not fully independent of other factors. These findings require further investigation to determine the hemodynamic benefits of aggressive phosphate lowering in ESRD and even possibly in pre-ESRD chronic kidney disease. They also introduce the possibility of more targeted approaches to BP management among patients with refractory hyperphosphatemia. Such research will require comprehensive assessment of the numerous mediators of MBD.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMineral Bone Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eESRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnd stage renal disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePTH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eParathyroid hormone\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEndothelial cell dysfunction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAsymmetric dimethyarginine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTPRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTotal peripheral resistance index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNICOM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNon-invasive cardiac output monitor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTPR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTotal peripheral resistance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean arterial pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiac output\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProtein catabolic rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eET-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEndothelin-1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGLM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneralized linear regression models\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAkaike Information Criteria\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRAAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRenin angiotensin aldosterone system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSNS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSympathetic nervous system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eStatement of Ethics: \u0026nbsp;The study protocol was reviewed and approved by the University of Texas Southwestern Medical Center Institutional Review Board approved the protocol (STU 052012-029 first approved 8/9/2012). \u0026nbsp;All participants provided written informed consent. \u0026nbsp;All procedures were in accordance with the Declaration of Helsinki. \u0026nbsp; The study was part of a registered clinical trial, NCT01862497 (May 24, 2013).\u003c/p\u003e\n\u003cp\u003eConsent for publication: not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of Data and materials: The datasets analyzed during the current study are available from the corresponding author on reasonable request. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting Interests: \u0026nbsp;Dr. Van Buren serves on the Editorial Board for BMC Nephrology, but there are no significant financial or non-financial competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding Sources: Funding for this study came from NIDDK 1K23DK096007-01A1 (PVB) and VA Merit CX002009-1 as well as support from the University of Texas Southwestern O\u0026rsquo;Brien Kidney Research Core (NIH grant P30DK079328). \u0026nbsp; Dr. Van Buren also receives institutional support from UT Southwestern as a Dedman Family Scholar in Clinical Care.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJJ: Writing-review and editing; presentation at ASN meeting\u003c/p\u003e\n\u003cp\u003eHJS: Formal Data analysis, writing review and editing\u003c/p\u003e\n\u003cp\u003eHN: Formal Data analysis, writing review and editing\u003c/p\u003e\n\u003cp\u003eJP, KS, SS: Investigation; Writing-review and editing\u003c/p\u003e\n\u003cp\u003ePVB: Conceptualization, Investigation, Project Administration, Data collection, Writing-original draft; review and editing\u003c/p\u003e\n\u003cp\u003eAcknowledgements: Data from this study was presented as a virtual poster at the American Society of Nephrology Kidney Week Meeting (November 2021). \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKalantar-Zadeh K, Kuwae N, Regidor D \u003cem\u003eet al.\u003c/em\u003e Survical predictability of time-varying indicators of bone disease in maintenance hemodialysis patients. Kidney International 2006; 70:771\u0026ndash;780.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShuto E, Taketani Y, Tanaka R \u003cem\u003eet al.\u003c/em\u003e Dietary Phosphorus Acutely Impairs Endothelial Function. J Am Soc Nephrol 2009; 20:1504\u0026ndash;1512.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgarwal R, Nissenson A, Batlle D \u003cem\u003eet al.\u003c/em\u003e Prevalence, Treatment, and Control of Hypertension in Chronic Hemodialysis Patients in the United States. American Journal of Medicine 2003; 115:291\u0026ndash;297.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerbeke F, Pannier B, Guerin A \u003cem\u003eet al.\u003c/em\u003e Flow-Mediated Vasodilation in End-Stage Renal Disease. Clin J Am Soc Nephrol 2011; 6:2009\u0026ndash;2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZoccali C, Bode-Boger S, Mallamaci F \u003cem\u003eet al.\u003c/em\u003e Plasma concentration of asymmetrical dimethylarginine and mortality in patients with end-stage renal disease: a prospective study. Lancet 2001; 358:2113\u0026ndash;2117.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoundation NK. KDOQI Clinical Practice Guidelines for Cardiovascular Disease in Dialysis Patients. American Journal of Kidney Diseases 2005; 45:S1-S154.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWith Intradialytic Hypertension. In: ClinicalTrials.gov [Internet]. Bethesda (MD): National Library of Medicine (US). 2000-[cited January 16, 2016] Available from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.clinicaltrials.gov/ct2/show/NCT01862497?term=van+buren\u0026amp;rank=2\u003c/span\u003e\u003cspan address=\"https://www.clinicaltrials.gov/ct2/show/NCT01862497?term=van+buren\u0026amp;rank=2\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e; NLM identifier NCT01862497 NIoDaDaKDNTUoTSMCaDMaToIABPiP.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInrig J, Patel U, Gillespie B \u003cem\u003eet al.\u003c/em\u003e Relationship between interdialytic weight gain and blood pressure among prevalent hemodialysis patients. Am J Kidney Dis 2007; 2007:108\u0026ndash;118.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKestenbaum B, Sampson J, Rudser K \u003cem\u003eet al.\u003c/em\u003e Serum Phosphate Levels and Mortality Risk Among People with Chronic Kidney Disease. J Am Soc Nephrol 2005; 16:520\u0026ndash;528.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBozic M, Panizo S, Sevilla M \u003cem\u003eet al.\u003c/em\u003e High phosphate diet increases arterial blood pressure via a parathyroid hormone mediated increase in renin. J Hypertens 2014; 32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohammad J, Scanni R, Bestmann L \u003cem\u003eet al.\u003c/em\u003e A Controlled Increase in Dietary Phosphate Elevates BP in Healthy Human Subjects. J Am Soc Nephrol 2019; 29:2089\u0026ndash;2098.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMendes M, Resende L, Teixeira A \u003cem\u003eet al.\u003c/em\u003e Blood pressure and phosphate level in diabetic and non-diabetic kidney disease: Results of the cross sectional \"Low Clearance Consultation\" study. Porto Biomedical Journal 2017; 2:301\u0026ndash;305.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang K, Cho S, Kim S, Lee Y. Serum Phosphorus Levels are Associated with Intradialytic Hypotension in Hemodialysis Patients. Nephron 2021; 145:238\u0026ndash;244.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNongnuch A, Campbell N, Stern E \u003cem\u003eet al.\u003c/em\u003e Increased postdialysis systolic blood pressure is associated with extracellular overhydration in hemodialysis outpatients. Kidney Int 2015; 87:452\u0026ndash;457.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMizuno M, Mitchell J, Crawford S \u003cem\u003eet al.\u003c/em\u003e High dietary phosphate intake induces hypertension and augments exercise pressor reflex function in rats. Am J Physiol Regul Integr Comp Physiol 2016; 311:R39-R48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim H, Mizuno M, Vongpatanasin W. Phosphate, the forgotten mineral in hypertension. Curr Opin Nephrol Hypertens 2019; 28:345\u0026ndash;351.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGinsberg C, Houben A, Malhotra R \u003cem\u003eet al.\u003c/em\u003e Serum Phosphate and Microvascular Function in a Population-Based Cohort. Clin J Am Soc Nephrol 2019; 14:1626\u0026ndash;1633.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDember L, Imrey P, Duess M \u003cem\u003eet al.\u003c/em\u003e Vascular Function at Baseline in the Hemodialysis Fistula Maturation Study. J Am Heart Assoc 2016; 5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZoccali C, Torino C, Curatola G \u003cem\u003eet al.\u003c/em\u003e Serum phosphate modifies the vascular response to vitamin D receptor activation in chronic kidney disease (CKD) patients. Nutrition, Metabolism, and Cardiovascular Disease 2016; 26:581\u0026ndash;589.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlmos G, Martinez-Miguel P, Alcalde-Estevez E \u003cem\u003eet al.\u003c/em\u003e Hyperphosphatemia induces senescence in human endothelial cells by increasing endothelin-1 production. Aging Cell 2017; 16:1300\u0026ndash;1312.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoen G, Mantella D, Sardella D \u003cem\u003eet al.\u003c/em\u003e Asymmetric dimethylarginine, vascular calcifications and parathyroid hormone serum levels in hemodialysis patients. Journal of Nephrology 2009; 22:616\u0026ndash;622.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaglar K, Yilmaz M, Saglam M \u003cem\u003eet al.\u003c/em\u003e Short-Term Treatment with Sevelamer Increases Serum Fetuin-A Concentration and Improves Endothelial Dysfunction in Chronic Kidney Disease 4 Patients. Clin J Am Soc Nephrol 2008; 3:61\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKovesdy C, Lu J, Wall B \u003cem\u003eet al.\u003c/em\u003e Changes with Lanthanum Carbonate, Calcium Acetate, and Phosphorus Restriction in CKD: A Randomized Controlled Trial. Kidney Int Rep 2018; 3:897\u0026ndash;904.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Phosphate, Hemodialysis, Endothelial Cell Dysfunction, Mineral Bone Disease, Vasoconstriction","lastPublishedDoi":"10.21203/rs.3.rs-1523519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1523519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\u003cp\u003eHyperphosphatemia occurs frequently in end-stage renal disease patients on hemodialysis and is associated with increased mortality.\u0026nbsp;Hyperphosphatemia contributes to vascular calcification in these patients, but there is emerging evidence that it is also associated with endothelial cell dysfunction.\u0026nbsp;\u003c/p\u003e\u003cp\u003eMethods\u003c/p\u003e\u003cp\u003eWe conducted a cross-sectional study in hypertensive hemodialysis patients.\u0026nbsp;We obtained pre-hemodialysis measurements of total peripheral resistance index (TPRI, non-invasive cardiac output monitor) and plasma levels of endothelin-1 (ET-1) and asymmetric dimethylarginine (ADMA).\u0026nbsp;We ascertained the routine peridialytic blood pressure (BP) measurements from that treatment and the most recent pre-hemodialysis serum phosphate levels.\u0026nbsp;We used generalized linear regression analyses to determine independent associations between serum phosphate with BP, TPRI, ET-1, and ADMA while controlling for demographic variables, parathyroid hormone (PTH), and interdialytic weight gain. \u003c/p\u003e\u003cp\u003eResults\u003c/p\u003e\u003cp\u003eThere were 54 patients analyzed.\u0026nbsp;Mean pre-HD supine and seated systolic and diastolic BP were 164 (27), 158 (21), 91.5 (17), and 86.1 (16) mmHg. Mean serum phosphate was 5.89 (1.8) mg/dL. There were significant correlations between phosphate with all pre-hemodialysis BP measurements (r=0.3, p=.04; r=0.4, p=.002; r=0.5, p\u0026lt;.0001; and r=0.5, p=.0003.)\u0026nbsp;The correlations with phosphate and TPRI, ET-1, and ADMA were 0.3 (p=.01), 0.4 (p=.007), and 0.3 (p=.04).\u0026nbsp;In our final linear regression analyses controlling for baseline characteristics, PTH, and interdialytic weight gain, independent associations between phosphate with pre-hemodialysis diastolic BP, TPRI, and ET-1 were retained (β=4.33, p=.0002; log transformed β=0.05, p=.005; reciprocal transformed β= -0.03, p=.047). \u0026nbsp;\u003c/p\u003e\u003cp\u003eConclusions\u003c/p\u003e\u003cp\u003eSerum phosphate concentration is independently associated with higher pre-HD BP, vasoconstriction, and markers of endothelial cell dysfunction.\u0026nbsp;These findings demonstrate an additional negative impact of hyperphosphatemia on cardiovascular health beyond vascular calcification. \u003c/p\u003e\u003cp\u003eThe study was part of a registered clinical trial, NCT01862497 (May 24, 2013).\u003c/p\u003e","manuscriptTitle":"Hyperphosphatemia and its Relationship with Blood Pressure, Vasoconstriction, and Endothelial Cell Dysfunction in Hypertensive Hemodialysis Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-04-11 17:00:38","doi":"10.21203/rs.3.rs-1523519/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-05-30T16:56:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-05-27T18:07:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1836218e-7ebf-48df-adea-8c40d5d19521","date":"2022-05-18T09:08:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-18T13:03:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"a314f047-238d-4704-a347-b898167403f8","date":"2022-04-12T12:55:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-04-10T02:19:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-04-10T01:22:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-04-08T19:30:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-04-08T19:20:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2022-04-04T22:37:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0f12ed91-8682-4ee2-9950-d27c22c442cd","owner":[],"postedDate":"April 11th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-08-05T16:44:17+00:00","versionOfRecord":[],"versionCreatedAt":"2022-04-11 17:00:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1523519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1523519","identity":"rs-1523519","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}